MCPHub LabRegistryelevenlabs-mcp
elevenlabs

elevenlabs mcp

Built by elevenlabs • 1,275 stars

What is elevenlabs mcp?

A high-performance MCP server implementation for elevenlabs-mcp that bridges the gap between the Model Context Protocol and external services. It allows Large Language Models to interact with your data and tools with low latency and native support.

How to use elevenlabs mcp?

1. Ensure you have an MCP-compatible client (like Claude Desktop) installed. 2. Configure your server with: npx @modelcontextprotocol/elevenlabs-mcp 3. Restart your client and verify the new tools are available in the system catalog.
šŸ›”ļø Scoped (Restricted)
npx @modelcontextprotocol/elevenlabs-mcp --scope restricted
šŸ”“ Unrestricted Access
npx @modelcontextprotocol/elevenlabs-mcp

Key Features

Native MCP Protocol Support
High-performance Data Streaming
Type-safe Tool Definitions
Seamless Environment Integration

Optimized Use Cases

Connecting external databases to AI workflows
Automating workflow tasks via natural language
Augmenting developer productivity with specialized tools

elevenlabs mcp FAQ

Q

What is an MCP server?

MCP is an open standard that enables developers to build secure, two-way integrations between AI models and local or remote data sources.

Q

Is this server ready for production?

Yes, this server follows standard MCP security patterns and tool-restricted access.

Official Documentation

View on GitHub

export

[!WARNING] This local MCP server is deprecated in favor of the ElevenLabs hosted MCP server.

The hosted server is available at https://api.elevenlabs.io/v1/mcp, with nothing to install or run locally. It authenticates with OAuth, so no API keys are copied into your client. See the hosted MCP server documentation to connect from Claude, Cursor, or any other MCP client.

This repository is no longer actively maintained.

<div class="title-block" style="text-align: center;" align="center">

Discord Community Twitter PyPI Tests

</div> <p align="center"> Official ElevenLabs <a href="https://github.com/modelcontextprotocol">Model Context Protocol (MCP)</a> server that enables interaction with powerful Text to Speech and audio processing APIs. This server allows MCP clients like <a href="https://www.anthropic.com/claude">Claude Desktop</a>, <a href="https://www.cursor.so">Cursor</a>, <a href="https://codeium.com/windsurf">Windsurf</a>, <a href="https://github.com/openai/openai-agents-python">OpenAI Agents</a> and others to generate speech, clone voices, transcribe audio, and more. </p> <!-- mcp-name: io.github.elevenlabs/elevenlabs-mcp -->

Quickstart with Claude Desktop

  1. Get your API key from ElevenLabs. There is a free tier with 10k credits per month.
  2. Install uv (Python package manager), install with curl -LsSf https://astral.sh/uv/install.sh | sh or see the uv repo for additional install methods.
  3. Go to Claude > Settings > Developer > Edit Config > claude_desktop_config.json to include the following:
{
  "mcpServers": {
    "ElevenLabs": {
      "command": "uvx",
      "args": ["elevenlabs-mcp"],
      "env": {
        "ELEVENLABS_API_KEY": "<insert-your-api-key-here>"
      }
    }
  }
}

If you're using Windows, you will have to enable "Developer Mode" in Claude Desktop to use the MCP server. Click "Help" in the hamburger menu at the top left and select "Enable Developer Mode".

Other MCP clients

For other clients like Cursor and Windsurf, run:

  1. pip install elevenlabs-mcp
  2. python -m elevenlabs_mcp --api-key={{PUT_YOUR_API_KEY_HERE}} --print to get the configuration. Paste it into appropriate configuration directory specified by your MCP client.

That's it. Your MCP client can now interact with ElevenLabs through these tools:

Example usage

āš ļø Warning: ElevenLabs credits are needed to use these tools.

Try asking Claude:

  • "Create an AI agent that speaks like a film noir detective and can answer questions about classic movies"
  • "Generate three voice variations for a wise, ancient dragon character, then I will choose my favorite voice to add to my voice library"
  • "Convert this recording of my voice to sound like a medieval knight"
  • "Create a soundscape of a thunderstorm in a dense jungle with animals reacting to the weather"
  • "Turn this speech into text, identify different speakers, then convert it back using unique voices for each person"

Optional features

File Output Configuration

You can configure how the MCP server handles file outputs using these environment variables in your claude_desktop_config.json:

  • ELEVENLABS_MCP_BASE_PATH: Specify the base path for file operations (default: ~/Desktop). This directory is also the security boundary for input files: any path passed to a tool that reads a local file (e.g. speech_to_text, isolate_audio, speech_to_speech, video_to_music, upload_music_for_inpainting) must resolve inside this directory, whether given as an absolute or relative path. Paths outside it — even if absolute and previously accepted — are rejected. Set this to a directory that contains everything you need to read from or write to.
  • ELEVENLABS_MCP_OUTPUT_MODE: Control how generated files are returned (default: files)

Output Modes

The ELEVENLABS_MCP_OUTPUT_MODE environment variable supports three modes:

  1. files (default): Save files to disk and return file paths

    "env": {
      "ELEVENLABS_API_KEY": "your-api-key",
      "ELEVENLABS_MCP_OUTPUT_MODE": "files"
    }
    
  2. resources: Return files as MCP resources; binary data is base64-encoded, text is returned as UTF-8 text

    "env": {
      "ELEVENLABS_API_KEY": "your-api-key",
      "ELEVENLABS_MCP_OUTPUT_MODE": "resources"
    }
    
  3. both: Save files to disk AND return as MCP resources

    "env": {
      "ELEVENLABS_API_KEY": "your-api-key",
      "ELEVENLABS_MCP_OUTPUT_MODE": "both"
    }
    

Resource Mode Benefits:

  • Files are returned directly in the MCP response as base64-encoded data
  • No disk I/O required - useful for containerized or serverless environments
  • MCP clients can access file content immediately without file system access
  • In both mode, resources can be fetched later using the elevenlabs://filename URI pattern

Use Cases:

  • files: Traditional file-based workflows, local development
  • resources: Cloud environments, MCP clients without file system access
  • both: Maximum flexibility, caching, and resource sharing scenarios

Data residency keys

You can specify the data residency region with the ELEVENLABS_API_RESIDENCY environment variable. Defaults to "us".

Note: Data residency is an enterprise only feature. See the docs for more details.

Contributing

If you want to contribute or run from source:

  1. Clone the repository:
git clone https://github.com/elevenlabs/elevenlabs-mcp
cd elevenlabs-mcp
  1. Create a virtual environment and install dependencies using uv:
uv venv
source .venv/bin/activate
uv pip install -e ".[dev]"
  1. Copy .env.example to .env and add your ElevenLabs API key:
cp .env.example .env
# Edit .env and add your API key
  1. Run the tests to make sure everything is working:
./scripts/test.sh
# Or with options
./scripts/test.sh --verbose --fail-fast
  1. Install the server in Claude Desktop: mcp install elevenlabs_mcp/server.py

  2. Debug and test locally with MCP Inspector: mcp dev elevenlabs_mcp/server.py

Troubleshooting

Logs when running with Claude Desktop can be found at:

  • Windows: %APPDATA%\Claude\logs\mcp-server-elevenlabs.log
  • macOS: ~/Library/Logs/Claude/mcp-server-elevenlabs.log

Timeouts when using certain tools

Certain ElevenLabs API operations, like voice design and audio isolation, can take a long time to resolve. When using the MCP inspector in dev mode, you might get timeout errors despite the tool completing its intended task.

This shouldn't occur when using a client like Claude.

MCP ElevenLabs: spawn uvx ENOENT

If you encounter the error "MCP ElevenLabs: spawn uvx ENOENT", confirm its absolute path by running this command in your terminal:

which uvx

Once you obtain the absolute path (e.g., /usr/local/bin/uvx), update your configuration to use that path (e.g., "command": "/usr/local/bin/uvx"). This ensures that the correct executable is referenced.

Global Ranking

7.1
Trust ScoreMCPHub Index

Based on codebase health & activity.

Manual Config

{ "mcpServers": { "elevenlabs-mcp": { "command": "npx", "args": ["elevenlabs-mcp"] } } }